Data Engineer

Role Overview

We are looking for a Data Engineer with 2–4 years of experience in building, maintaining, and optimizing data solutions on Microsoft platforms. The ideal candidate should have hands-on experience with Azure data services, SQL-based development, ETL/ELT pipelines, data warehousing concepts, and reporting integration. This role will work closely with data analysts, business teams, and application teams to deliver reliable, scalable, and secure data solutions.

Responsibilities

• Design, develop, and maintain data pipelines using Microsoft Azure data services such as Azure Data Factory, Azure Data Lake, and Azure SQL Database.
• Build ETL/ELT processes to ingest, transform, validate, and load data from multiple structured and semi-structured sources.
• Develop and optimize SQL queries, stored procedures, views, and data models to support analytics and reporting needs.
• Support data warehouse and data lake implementations, including data integration, data cleansing, and data quality checks.
• Collaborate with business analysts, data analysts, and application teams to understand data requirements and deliver reusable data assets.
• Monitor data pipelines, troubleshoot failures, and implement performance improvements.
• Ensure data security, access controls, and compliance with organizational data governance standards.
• Create and maintain technical documentation for data flows, source-to-target mappings, data models, and operational procedures.
• Support Power BI datasets and reporting teams by preparing reliable and performance-optimized data layers.

Requirements

• Bachelor’s degree in Computer Science, Information Technology, Engineering, Data Science, or a related discipline.
• 2–4 years of relevant experience in data engineering, database development, ETL development, or data warehousing projects.
• Hands-on experience working on Microsoft technology stack projects is required.
• Strong hands-on experience with SQL Server, T-SQL, stored procedures, functions, indexing, and query optimization.
• Working knowledge of Azure Data Factory for pipeline development, orchestration, scheduling, and monitoring.
• Experience with Azure SQL Database, Azure Data Lake Storage, or related Microsoft data services.
• Good understanding of ETL/ELT concepts, data warehousing, dimensional modeling, star schema, and incremental data loads.
• Exposure to Power BI data preparation, semantic models, datasets, or reporting integration.
• Basic to intermediate programming or scripting experience using Python, PySpark, or C# is preferred.
• Familiarity with Git, Azure DevOps, CI/CD concepts, and Agile delivery practices.

Skills

• Azure Data Factory
• SQL Server
• Python
• Power BI
• ETL/ELT